Radware Doubles DDoS Mitigation Capacity as AI-Powered Attacks Surge

The cloud security landscape is facing a scalability crisis. As distributed denial-of-service (DDoS) attacks grow not just in volume but in intelligence and persistence, leading security providers are being forced to make monumental infrastructure investments just to keep pace. Radware's recent announcement that it has doubled its global cloud DDoS mitigation capacity is a stark indicator of this new reality—a defensive arms race fueled by offensive innovation, particularly from AI-powered tools.

This expansion is a direct response to a threat environment that has fundamentally shifted. The era of simple volumetric floods is giving way to complex, multi-vector campaigns that combine high packet-per-second rates with sophisticated application-layer (Layer 7) attacks designed to mimic legitimate traffic. These assaults, often orchestrated by botnets enhanced with AI algorithms, can adapt in real-time, evading static, signature-based defenses and probing for weaknesses with unprecedented efficiency.

Radware's strategy goes beyond merely provisioning more bandwidth. The doubling of capacity is built upon the scaling of its core security technologies across an expanded global network of scrubbing centers. Central to this is the company's behavioral-based detection engine, which analyzes traffic patterns to identify anomalies indicative of an attack, rather than relying on known threat signatures. This approach is crucial for catching novel, AI-generated attack vectors. Coupled with automated mitigation workflows, the system aims to identify and neutralize threats within seconds, minimizing potential downtime for protected organizations.

The implications for the cybersecurity community are profound. First, it sets a new benchmark for infrastructure scale in the DDoS mitigation market. Competitors and cloud providers will face pressure to match this level of investment, potentially triggering a wave of capacity announcements across the sector. Second, it raises urgent questions about economic sustainability. Building and operating a global network of high-capacity scrubbing centers is extraordinarily capital- and resource-intensive. The cost of this defensive scaling will inevitably be passed on to enterprises, making robust DDoS protection a more significant line item in security budgets.

Furthermore, this move highlights the critical importance of architectural resilience. For enterprises, reliance on a single cloud provider or a monolithic security solution is becoming increasingly risky. Radware's expansion underscores the value of distributed, cloud-native mitigation networks that can absorb and disperse attack traffic globally. Security architects must now design for failure and scale, incorporating multi-cloud strategies and redundant mitigation services to ensure business continuity.

The escalation also points to a broader trend: the weaponization of AI in cyber conflict. Attackers are using machine learning to optimize attack patterns, identify target vulnerabilities faster, and generate malicious traffic that is harder to distinguish from normal user behavior. Defenders, in turn, are deploying AI for behavioral analytics and automated response. Radware's capacity doubling is, in part, an infrastructure prerequisite to support the computational demands of these advanced defensive AI systems.

In conclusion, Radware's massive infrastructure investment is less a corporate milestone and more a canary in the coal mine for the entire industry. It signals that the current trajectory of DDoS attack growth—supercharged by accessible AI tools—is pushing cloud security defenses to their practical and economic limits. For CISOs and network engineers, the message is clear: the assumptions about attack scale from just a few years ago are obsolete. Strategic planning must now account for an era of hyper-scale threats, where defensive capacity, intelligent automation, and architectural dispersion are not just advantages, but fundamental requirements for survival.